from IPython.display import HTML
HTML('''<script>
code_show=true;
function code_toggle() {
if (code_show){
$('div.input').hide();
} else {
$('div.input').show();
}
code_show = !code_show
}
$( document ).ready(code_toggle);
</script>
<form action="javascript:code_toggle()"><input type="submit" value="Click here to toggle on/off the raw code."></form>''')
from IPython.display import HTML
HTML('''<script> $('div .input').hide()''')
bar_plots = [
go.Bar(x = df['Year'], y = df['Ave. Usage/P (kWh/p)'],name='Total Consumption (kWh)')
]
layout = go.Layout(
title=go.layout.Title(text='Monthly Average Person Electricity Consumption In Respective Year',x=0.5),
yaxis_title='Usage (kWh/person)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
#fig.show()
bar_plots = [
go.Bar(x = df['Year'], y = df['Ave. Usage/A (kWh/m2)'],name='Total Consumption (kWh)')
]
layout = go.Layout(
title=go.layout.Title(text='Monthly Average Electricity Consumption/Area In Respective Year',x=0.5),
yaxis_title='Usage (kWh/m2)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
bar_plots = [
go.Bar(x = df['Year'], y = df['Total Usage (kWh)'],name='Total Consumption (kWh)'),
go.Bar(x = df['Year'], y = df['Total Amount (RM)'],name='Total Amount (RM)')
]
layout = go.Layout(
title=go.layout.Title(text='Annual Electricity Consumption (kWh) & Amount (RM)',x=0.5),
yaxis_title='Usage (kWh)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
bar_plots = [
go.Bar(x = df1[2014], y = df1['Usage (kWh)'],name=2014),
go.Bar(x = df2[2015], y = df2['Usage (kWh)'],name=2015),
go.Bar(x = df3[2016], y = df3['Usage (kWh)'],name=2016),
go.Bar(x = df4[2017], y = df4['Usage (kWh)'],name=2017),
go.Bar(x = df5[2018], y = df5['Usage (kWh)'],name=2018),
go.Bar(x = df6[2019], y = df6['Usage (kWh)'],name=2019),
go.Bar(x = df7[2020], y = df7['Usage (kWh)'],name=2020),
go.Bar(x = df8[2021], y = df8['Usage (kWh)'],name=2021),
go.Bar(x = df9[2022], y = df9['Usage (kWh)'],name=2022)
]
layout = go.Layout(
title=go.layout.Title(text='Monthly Electricity Consumption (kWh)',x=0.5),
yaxis_title='Usage (kWh)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
bar_plots = [
go.Bar(x = df1[2014], y = df1['Amount (RM)'],name=2014),
go.Bar(x = df2[2015], y = df2['Amount (RM)'],name=2015),
go.Bar(x = df3[2016], y = df3['Amount (RM)'],name=2016),
go.Bar(x = df4[2017], y = df4['Amount (RM)'],name=2017),
go.Bar(x = df5[2018], y = df5['Amount (RM)'],name=2018),
go.Bar(x = df6[2019], y = df6['Amount (RM)'],name=2019),
go.Bar(x = df7[2020], y = df7['Amount (RM)'],name=2020),
go.Bar(x = df8[2021], y = df8['Amount (RM)'],name=2021),
go.Bar(x = df9[2022], y = df9['Amount (RM)'],name=2022)
]
layout = go.Layout(
title=go.layout.Title(text='Monthly Electricity Amount (RM)',x=0.5),
yaxis_title='Amount (RM)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
df1['kWh/person'] = df1['Usage (kWh)']/5
df2['kWh/person'] = df2['Usage (kWh)']/5
df3['kWh/person'] = df3['Usage (kWh)']/5
df4['kWh/person'] = df4['Usage (kWh)']/5
df5['kWh/person'] = df5['Usage (kWh)']/5
df6['kWh/person'] = df6['Usage (kWh)']/5
df7['kWh/person'] = df7['Usage (kWh)']/5
df8['kWh/person'] = df8['Usage (kWh)']/5
df9['kWh/person'] = df9['Usage (kWh)']/5
display_side_by_side(df1, df2, df3)
| 2014 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 261 | 63.98 | 52.2 |
| 1 | Feb | 288 | 70.56 | 57.6 |
| 2 | Mac | 348 | 101.77 | 69.6 |
| 3 | Apr | 263 | 64.64 | 52.6 |
| 4 | May | 350 | 102.80 | 70.0 |
| 5 | Jun | 324 | 89.38 | 64.8 |
| 6 | Jul | 346 | 100.74 | 69.2 |
| 7 | Aug | 268 | 66.31 | 53.6 |
| 8 | Sep | 292 | 74.33 | 58.4 |
| 9 | Oct | 267 | 65.98 | 53.4 |
| 10 | Nov | 301 | 77.52 | 60.2 |
| 11 | Dec | 337 | 86.34 | 67.4 |
| 2015 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 254 | 61.64 | 50.8 |
| 1 | Feb | 347 | 86.90 | 69.4 |
| 2 | Mac | 276 | 68.98 | 55.2 |
| 3 | Apr | 309 | 81.64 | 61.8 |
| 4 | May | 301 | 77.52 | 60.2 |
| 5 | Jun | 273 | 67.98 | 54.6 |
| 6 | Jul | 405 | 103.84 | 81.0 |
| 7 | Aug | 238 | 56.29 | 47.6 |
| 8 | Sep | 295 | 75.33 | 59.0 |
| 9 | Oct | 266 | 65.64 | 53.2 |
| 10 | Nov | 321 | 81.69 | 64.2 |
| 11 | Dec | 284 | 71.66 | 56.8 |
| 2016 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 246 | 58.96 | 49.2 |
| 1 | Feb | 399 | 120.01 | 79.8 |
| 2 | Mac | 530 | 188.20 | 106.0 |
| 3 | Apr | 465 | 162.14 | 93.0 |
| 4 | May | 494 | 177.10 | 98.8 |
| 5 | Jun | 342 | 98.67 | 68.4 |
| 6 | Jul | 305 | 79.58 | 61.0 |
| 7 | Aug | 409 | 125.46 | 81.8 |
| 8 | Sep | 336 | 87.80 | 67.2 |
| 9 | Oct | 378 | 117.25 | 75.6 |
| 10 | Nov | 286 | 72.32 | 57.2 |
| 11 | Dec | 308 | 78.16 | 61.6 |
display_side_by_side(df4, df5, df6)
| 2017 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 427 | 142.53 | 85.4 |
| 1 | Feb | 390 | 123.44 | 78.0 |
| 2 | Mac | 448 | 153.37 | 89.6 |
| 3 | Apr | 441 | 149.76 | 88.2 |
| 4 | May | 361 | 108.48 | 72.2 |
| 5 | Jun | 393 | 124.99 | 78.6 |
| 6 | Jul | 339 | 91.97 | 67.8 |
| 7 | Aug | 383 | 119.83 | 76.6 |
| 8 | Sep | 399 | 122.93 | 79.8 |
| 9 | Oct | 406 | 131.70 | 81.2 |
| 10 | Nov | 405 | 131.18 | 81.0 |
| 11 | Dec | 327 | 90.93 | 65.4 |
| 2018 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 342 | 98.67 | 68.4 |
| 1 | Feb | 455 | 149.20 | 91.0 |
| 2 | Mac | 426 | 142.02 | 85.2 |
| 3 | Apr | 419 | 138.40 | 83.8 |
| 4 | May | 490 | 175.04 | 98.0 |
| 5 | Jun | 315 | 78.88 | 63.0 |
| 6 | Jul | 357 | 106.41 | 71.4 |
| 7 | Aug | 412 | 134.79 | 82.4 |
| 8 | Sep | 389 | 115.14 | 77.8 |
| 9 | Oct | 358 | 106.93 | 71.6 |
| 10 | Nov | 368 | 112.09 | 73.6 |
| 11 | Dec | 309 | 81.64 | 61.8 |
| 2019 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 370 | 113.12 | 74.0 |
| 1 | Feb | 444 | 151.30 | 88.8 |
| 2 | Mac | 399 | 130.15 | 79.8 |
| 3 | Apr | 373 | 116.50 | 74.6 |
| 4 | May | 413 | 137.45 | 82.6 |
| 5 | Jun | 285 | 72.00 | 57.0 |
| 6 | Jul | 366 | 112.85 | 73.2 |
| 7 | Aug | 280 | 70.30 | 56.0 |
| 8 | Sep | 348 | 103.40 | 69.6 |
| 9 | Oct | 336 | 97.10 | 67.2 |
| 10 | Nov | 323 | 90.30 | 64.6 |
| 11 | Dec | 312 | 84.50 | 62.4 |
display_side_by_side(df7, df8, df9)
| 2020 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 355 | 107.05 | 71.0 |
| 1 | Feb | 314 | 85.55 | 62.8 |
| 2 | Mac | 350 | 104.45 | 70.0 |
| 3 | Apr | 350 | 96.35 | 70.0 |
| 4 | May | 350 | 88.80 | 70.0 |
| 5 | Jun | 1221 | 164.40 | 244.2 |
| 6 | Jul | 368 | 112.10 | 73.6 |
| 7 | Aug | 344 | 99.70 | 68.8 |
| 8 | Sep | 360 | 107.96 | 72.0 |
| 9 | Oct | 336 | 82.55 | 67.2 |
| 10 | Nov | 391 | 107.05 | 78.2 |
| 11 | Dec | 341 | 84.80 | 68.2 |
| 2021 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 322 | 79.55 | 64.4 |
| 1 | Feb | 378 | 111.55 | 75.6 |
| 2 | Mac | 378 | 111.55 | 75.6 |
| 3 | Apr | 361 | 103.00 | 72.2 |
| 4 | May | 357 | 100.95 | 71.4 |
| 5 | Jun | 393 | 119.15 | 78.6 |
| 6 | Jul | 361 | 103.00 | 72.2 |
| 7 | Aug | 436 | 122.28 | 87.2 |
| 8 | Sep | 396 | 108.60 | 79.2 |
| 9 | Oct | 444 | 136.60 | 88.8 |
| 10 | Nov | 404 | 124.65 | 80.8 |
| 11 | Dec | 366 | 105.50 | 73.2 |
| 2022 | Usage (kWh) | Amount (RM) | kWh/person | |
|---|---|---|---|---|
| 0 | Jan | 359.0 | 102.00 | 71.8 |
| 1 | Feb | 323.0 | 83.85 | 64.6 |
| 2 | Mac | 384.0 | 114.60 | 76.8 |
| 3 | Apr | 460.0 | 152.91 | 92.0 |
| 4 | May | NaN | NaN | NaN |
| 5 | Jun | NaN | NaN | NaN |
| 6 | Jul | NaN | NaN | NaN |
| 7 | Aug | NaN | NaN | NaN |
| 8 | Sep | NaN | NaN | NaN |
| 9 | Oct | NaN | NaN | NaN |
| 10 | Nov | NaN | NaN | NaN |
| 11 | Dec | NaN | NaN | NaN |
bar_plots = [
go.Bar(x = df1[2014], y = df1['kWh/person'],name=2014),
go.Bar(x = df2[2015], y = df2['kWh/person'],name=2015),
go.Bar(x = df3[2016], y = df3['kWh/person'],name=2016),
go.Bar(x = df4[2017], y = df4['kWh/person'],name=2017),
go.Bar(x = df5[2018], y = df5['kWh/person'],name=2018),
go.Bar(x = df6[2019], y = df6['kWh/person'],name=2019),
go.Bar(x = df7[2020], y = df7['kWh/person'],name=2020),
go.Bar(x = df8[2021], y = df8['kWh/person'],name=2021),
go.Bar(x = df9[2022], y = df9['kWh/person'],name=2022)
]
layout = go.Layout(
title=go.layout.Title(text='Monthly kwh/person Usage',x=0.5),
yaxis_title='kWh/person',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
px.bar(df1, x = 2014, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2014, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df2, x = 2015, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2015, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df3, x = 2016, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2016, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df4, x = 2017, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2017, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df5, x = 2018, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2018, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df6, x = 2019, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2019, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df7, x = 2020, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2020, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df8, x = 2021, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2021, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df9, x = 2022, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2022, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df1, x = 2014, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2014, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df2, x = 2015, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2015, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df3, x = 2016, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2016, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df4, x = 2017, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2017, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df5, x = 2018, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2018, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df6, x = 2019, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2019, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df7, x = 2020, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2020, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df8, x = 2021, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2021, color_continuous_scale=px.colors.sequential.Viridis)
px.bar(df9, x = 2022, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2022, color_continuous_scale=px.colors.sequential.Viridis)
Note: This report is prepared by Zahiruddin Zahidanishah. This report is only for educational purposed and shall not be used for any commercial purposed.